Recently, virtualization of open systems and servers has been popularized, thereby complicating management of systems. In view of making it easier to manage the systems and of flexibly coping with a rapid increase in data capacity, storage systems have been commonly introduced.
In such storage systems, disks having different speeds can be used. Examples of the disks include a solid state disk (SSD), a serial attached small computer interface hard disk drive (SASHDD), and a serial advanced technology attachment (SATA) HDD.
In such a storage system, a storage area called a volume is created in some cases using a plurality of types of disks having different speeds included in the storage system. Automatic storage layering techniques have been widely used in which a storage area of data in the disks having different speeds in the volume is determined in accordance with a frequency of use of the data.
When the automatic disk layering technique is used, frequently used data is stored in a disk having a high speed in the volume while less frequently used data is stored in a disk having a low speed in the volume, for example. The automatic storage layering can achieve a storage device having a high speed and high capacity at low cost.
In an example of a storage performance adjusting technique, a limitation of a bandwidth of a data transfer path between the volume and a server that executes applications is adjusted. This function is called a quality of service (QoS) in some times.
In an example of the conventional automatic storage layering technique, a tier level is changed on the basis of a state of an application that accesses data in the volume. In another conventional technique, a virtual volume is clustered and segments are restructured by comparing measured loads of the respective clusters with a frequency of use of the virtual volume. In still another conventional technique, a location of data is determined on the basis of whether a target value is satisfied in a storage area to which the target value of a service level is allocated.
Patent Document 1: Japanese Laid-open Patent Publication No. 2011-70628
Patent Document 2: Japanese National Publication of International Patent Application No. 2012-509538 Patent Document 3: Japanese Laid-open Patent Publication No. 2008-27233
In the conventional automatic storage layering, input output per second (IOPS) thresholds and allocation rates of the disks in the volume are used as evaluation indicators. It is, thus, difficult for an operator to appropriately set the values. In the automatic storage layering, the IOPS is often used as the evaluation indicator of performance adjustment, for example. In the use of the QoS function, a response time is often used as the evaluation indicator of the performance adjustment. As a result, when performing the performance adjustment using both of the automatic storage layering function and the QoS function, the operator of the storage sets evaluation indicators that differ from each other for the respective functions. Both of the automatic layering function and the QoS function are functions that adjust the performance of the storage. It is thus cumbersome for the operator to use the respective functions in a different manner in the performance adjustment.
For the conventional technique in which the tier level is changed on the basis of the state of an application, it is difficult to readily perform the performance adjustment because setting a performance target and adjusting an actual measured performance in accordance with the performance target have not been taken into consideration. For the conventional technique in which a measured load serving as a performance indicator is compared with the frequency of use of the virtual volume and the segments are re-constructed, it is difficult to readily perform the performance adjustment because setting a target value and causing the actual measured performance to get close to the target value have not been taken into consideration. In the conventional technique in which the location of data is determined on the basis of whether the target value of the service level is satisfied, the data is stored when the target value is satisfied. It is, however, difficult to perform performance adjustment such that an actual measured performance gets close to the set target value.